Next Article in Journal
Experimental Investigation of the Prestrike Characteristics of a Double-Break Vacuum Circuit Breaker under DC Voltages
Next Article in Special Issue
Short-Term Forecasting of Large-Scale Clouds Impact on Downwelling Surface Solar Irradiation
Previous Article in Journal
Study on Characteristic and Energy of Argillaceous Weakly Cemented Rock under Dynamic Loading by Hopkinson Bar Experiment
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Evaluation of Mathematical Model to Characterize the Performance of Conventional and Hybrid PV Array Topologies under Static and Dynamic Shading Patterns

by
Manoharan Premkumar
1,
Umashankar Subramaniam
2,
Thanikanti Sudhakar Babu
3,
Rajvikram Madurai Elavarasan
4,* and
Lucian Mihet-Popa
5,*
1
Department of Electrical and Electronics Engineering, GMR Institute of Technology, Rajam, Andhra Pradesh 532127, India
2
Renewable Energy Laboratory, Prince Sultan University, Salahuddin, Riyadh 12435, Saudi Arabia
3
Department of Electrical Power Engineering, University Tenaga Nasional, Kajang 43000, Selangor, Malaysia
4
Department of Electrical and Electronics Engineering, Sri Venkateswara College of Engineering, Tamil Nadu 602117, India
5
Faculty of Electrical Engineering, Ostfold University College, NO-1757 Halden, Norway
*
Authors to whom correspondence should be addressed.
Energies 2020, 13(12), 3216; https://doi.org/10.3390/en13123216
Submission received: 26 May 2020 / Revised: 12 June 2020 / Accepted: 19 June 2020 / Published: 20 June 2020

Abstract

:
The analysis and the assessment of interconnected photovoltaic (PV) modules under different shading conditions and various shading patterns are presented in this paper. The partial shading conditions (PSCs) due to the various factors reduce the power output of PV arrays, and its characteristics have multiple peaks due to the mismatching losses between PV panels. The principal objective of this paper is to model, analyze, simulate and evaluate the performance of PV array topologies such as series-parallel (SP), honey-comb (HC), total-cross-tied (TCT), ladder (LD) and bridge-linked (BL) under different shading patterns to produce the maximum power by reducing the mismatching losses (MLs). Along with the conventional PV array topologies, this paper also discusses the hybrid PV array topologies such as bridge-linked honey-comb (BLHC), bridge-linked total-cross-tied (BLTCT) and series-parallel total-cross-tied (SPTCT). The performance analysis of the traditional PV array topologies along with the hybrid topologies is carried out during static and dynamic shading patterns by comparing the various parameters such as the global peak (GP), local peaks (LPs), corresponding voltage and current at GP and LPs, fill factor (FF) and ML. In addition, the voltage and current equations of the HC configuration under two shading conditions are derived, which represents one of the novelties of this paper. The various parameters of the SPR-200-BLK-U PV module are used for PV modeling and simulation in MATLAB/Simulink software. Thus, the obtained results provide useful information to the researchers for healthy operation and power maximization of PV systems.

Graphical Abstract

1. Introduction

India has always been a prominent country in terms of renewable energy aspects especially solar and wind in comparison with other countries in the world [1]. There are also some significant states in India, where solar energy resource was a vital source and whose solar potential is also high [2,3]. The solar photovoltaic (PV) power generation has been attracting because of the reduction in the PV module price, government incentives and innovative commercial models. However, the solar PV power generation systems have demerits, such as low energy conversion and high installation cost. The PV module has a non-linear voltage–current (V–I) characteristic, and there must be a maximum operating point on the power–voltage (P–V) characteristic. The power output of the PV module depends on the temperature and solar insolation. To improve the efficiency of the PV system, the module should be operated at the maximum power point [4,5,6,7]. However, the effectiveness of the system is reduced by a partial shading effect on the module/array. This shading effect is due to various factors such as building, tree, cloud, dust, etc. Due to partial shading conditions (PSCs), there are many peaks on the V–I and P–V characteristics of the PV module/array, which reduces the output power of the PV system [8,9].
Out of various factors that affect the performance of the PV module, the change in solar insolation and temperature are considered as critical factors. Under uniform irradiation, the PV panel exhibits a single maximum power point (MPP). Additionally, the MPP can be tracked using conventional methods such as perturb & observation, incremental conductance algorithm, etc. [10,11]. During PSCs, the PV panels exhibit multiple local peaks (LPs) and one global peak (GP), as discussed earlier. Due to multiple LPs, the PV system misleads the conventional maximum power point tracking (MPPT) techniques. In order to track the GP, the advanced MPPT techniques are effectively used [12,13,14,15,16,17,18,19,20]. Due to PSCs, the panel mismatching power loss is more, and hence the efficiency and capability to generate the maximum power are reduced. These problems can be overcome by connecting bypass diodes across the panel. However, the total effects can be overcome by connecting bypass diodes across each cell. Since it is not economical, the bypass diodes are connected across the group of cells. Some of the manufacturers are providing the PV module with two or three bypass diodes. In addition to PSC, power loss is also due to other factors, such as soiling, dust, bypass diode degradation, etc. [21]. The power loss can be reduced by the different PV array configurations, MPPTs, PV system architecture and converter topologies. Out of which, the different PV array configuration is one of the optimum ways that can reduce mismatching losses under PSCs. The PV array configurations are based on different electrical interconnection between the PV panels [22,23,24,25,26,27,28]. The PV architecture defines different methods of connecting power converters to the PV module/array, i.e., central level inverter, string inverter and microinverter [3]. The various MPPT techniques, such as distributed MPPT, central-level MPPT, module-level MPPT and reconfigurable MPPT, are also developed to reduce the mismatching losses (MLs) [29,30]. The PV arrays are formed using different configurations such as series-parallel (SP), total-cross-tied (TCT), bridge-linked (BL), honey-comb (HC) and ladder (LD) to attain the desired output voltage and current for grid-tied systems or standalone systems. The classification of the different configurations is given in Figure 1. The panels are connected in series to make a string, and the strings are connected in parallel to each other to get the desired voltage and current in SP array configurations. In the TCT array configuration, all nodes of rows are shortened in the SP array. The node voltages of all nodes and the sum of currents at various junctions are the same. In the BL configuration, the modules are connected in the form of a bridge rectifier in which the first few panels are connected in series and parallel to each other. By combining the advantages of TCT and BL, a modified BL configuration, named HC, is formulated [31,32,33,34].
The authors of [30,35] have discussed the ladder structure of the PV array to extract high output power during PSCs. The authors of [36,37] have discussed hybrid solar PV array topologies such as bridge-linked honey-comb (BLHC), bridge-linked total-cross-tied (BLTCT) and series-parallel total-cross-tied (SPTCT) configurations. The combination of BL and HC configuration is called BLHC, which has advantages of both BL and HC array configurations. The combination of BL and TCT configuration is called BLTCT and the combinations of SP and TCT configuration is called SPTCT configuration. These hybrid configurations are proposed by the researchers to minimize the panel mismatching losses, and these configurations are more competitive to the conventional PV array configurations. The authors of [38,39] investigated the PSC effect on the SP PV array configuration. The authors of [40] investigated the PSC effects on various PV array configurations such as SP, TCT and BL (6 × 2, 4 × 3, 2 × 6 and 3 × 4 array size). The authors of [41,42] presented a method to improve the power output during PSCs. Many studies have been conducted on the various PV array configurations under PSCs, and from each study, the superiority of the respective configuration is proved through a sequence of simulations. The researchers use a different method such as different PV array configurations, reconfigurable PV array topologies and different MPPT techniques to reduce mismatching loss, and the same can be explained briefly as follows.
(a)
Comparison of different PV array configurations
The author of [43] discussed a comparison between the various array configurations such as the series (S) PV array and SP PV array under PSCs. The modeling is done with the help of MATLAB/Simulink. The author concluded that the magnitude of GP depends on the shading pattern and array configurations. A detailed comparison is made on different PV array configurations under even and uneven column and row shadings [9]. The author concluded that out of different configurations, TCT array configuration is performing better under the different shading patterns. However, the author of [44] strongly disagrees with the widely held findings that SP PV array configuration is a highly efficient configuration in extracting maximum output power from the PV array. The author of [45] reviewed and generated M-code to study and compare the effects of PSCs on different PV array configurations. According to the author, HC and TCT are more effective than the other configurations under symmetric and asymmetric PV array configurations. The author of [24] discussed the performance comparison of the different PV array configurations such as S, SP, TCT, BL and HC under PSCs. The author also discussed non-linear equation solving using the Newton–Raphson algorithm. The authors of [46] discussed various PV array configuration and suggested to employ current injection technique to diminish the effect of PSCs on the PV array. The authors of [47] presented two types of PV array configurations, such as TCT and non-symmetrical, and tested on various shaded patterns to check the effectiveness of the array configurations, and proved that non-symmetrical configurations perform better than the TCT configuration. The authors of [48,49,50,51] discussed PV array topologies such as SP, BL, TCT and all authors claimed that TCT configuration performs better than the other configurations. The authors of [52,53,54,55,56] discussed a detailed procedure for modeling the PV array of any configuration, which is operating under uniform or PSCs. The authors of [57] presented an array of parallel-connected PV cells along with a low input voltage boost converter, and a wide bandwidth MPP technique to improve the output power of the PV array during PSCs and rapid shadow conditions. The model to find an optimal photovoltaic system configuration for the specified installation area that makes maximum profit over a lifetime of the PV energy plant is discussed in [58].
(b)
Modern PV array configurations
The author of [59] discussed a dynamic PV array reconfiguration system for the building-integrated PV systems and large PV plants. However, the operational and running cost of the systems and system complexity is more. The author of [60] discussed a technique to produce the maximum output power under PSCs. The method is employed with TCT configurations, but the physical location of the panel is rearranged based on the SU-DO-KU puzzle. However, due to the additional wiring requirements and unsuccessful distribution of shading, this method is not preferred. Modified SU-DO-KU based reconfiguration was proposed by [61]. It uses fixed reconfiguration, and it enhances the PV output power under mutual shading patterns. It overcomes the drawbacks of the conventional SU-DO-KU based PV array reconfigurations. The authors of [62,63,64,65] presented an adaptive PV reconfiguration under PSCs and malfunctioning situations. This technique divides the PV panel into the adaptive bank and fixed panels. If the fixed PV panels are shaded, the shaded panels are connected to the unshaded panels in the adaptive bank. However, this method requires additional sensors and switches for the implementation. Recently, the authors of [66] proposed an improved SU-DO-KU technique, and the technique was tested on 9 × 9 TCT PV array configuration to generate high output power under PSCs. The authors of [67] discussed a dynamical PV array reconfiguration strategy for a grid-tied PV system, and this reconfiguration is based on a plant-oriented configuration, which improves the energy production when the operating environmental situations are different. The authors of [68] discussed an adaptive reconfiguration scheme to reduce the effect of PSCs, in which a switching matrix attaches an adaptive bank to a static portion of the PV array based on a model control algorithm that improves the output power of the PV array. The authors of [69] proposed a magic square method to increase the output power by reconfiguring the location of the panels in the TCT PV array configuration. The authors of [70] proposed a new reconfiguration technique to ensure a minimum deviation from the nominal operating voltage, which improves the power output, and the same can be tested on a 4 × 4 PV cell array. The authors [71] disperse the power loss of a partially shaded PV array by reconfiguring a BLTCT hybrid topology-based mostly on the SU-DO-KU puzzle, which is known as SU-DO-KU ’s BLTCT reconfigured configuration. The authors of [72] proposed a new method to predict the connection of modules into a TCT PV array. In this approach, shaded and un-shaded modules are placed in an array in such a way that the shading effects are evenly distributed in each row, thereby increasing the power of the PV array.
(c)
MPPT techniques to extract more power
The author of [13,73,74] reviewed different MPPT algorithms such as P&O and incremental conductance that are implemented on the power converters to produce more energy from the PV array by matching the input impedance of the converter to match the GP of the array. The authors of [75] presented a bidirectional DC–DC converter, which helps the renewable energy systems, especially for the solar PV system to minimize the losses in the system. The author of [76] proposed a module integrated converter with MPPT architecture to generate the highest power than the conventional string or central inverter. The converter has its own MPPT controller for the single PV module, and all the converters are connected to the common bus. The drawback is that the cost of the microconverter-based PV system is higher. The authors of [77] proposed an accelerated optimization algorithm to extract the maximum power and minimize the mismatching losses of the PV system. The author of [78] reviewed a specific conventional and modern hybrid MPPT technique to extract the high output power from the PV modules. The study guides the researcher to select the proper MPPT technique for the PV systems. However, the researchers are confused about choosing the exact MPPT technique due to the rapid research in the field of MPPTs.
After reviewing various methods, the array configuration-based methods are useful and viable for the PV systems. Moreover, it helps the conventional/modern MPPT controllers to extract the maximum output power from the PV string/array and reduces the module MLs. However, mathematical analysis is required for the readers for a better understanding of the characteristics of array configurations under PSCs. In this paper, mathematical modeling, analysis, and simulations are carried out on the various array topologies, and performance assessment is carried out on the 4 × 4 PV array. The different PV array topologies are shown in Figure 2.
The mathematical modeling of the HC PV array configuration is not discussed in any of the literature. Therefore, in this paper, the HC PV array configuration is elaborately discussed, and the same has been analyzed and simulated using MATLAB/Simulink. In most of the literature, the authors confirmed that TCT configuration is better in terms of ML and FF. However, this paper also discusses various hybrid configurations (such as SPTCT, BLHC, and BLTCT) along with one new conventional LD configuration, which is more competitive to TCT. To validate and assess the performance of all the conventional topologies and hybrid topologies, an extensive simulation is carried out under various shading patterns such as an uneven row shading (URS), uneven column shading (UCS), uneven corner shading (UCRS), diagonal shading (DS) and random shadings (R-I and R-II). As presented in Figure 1, the performance assessment has been carried out in terms of open-circuit voltage (Voc), short circuit current (Isc), GP, LPs and its corresponding voltage and current (Vmpp and Impp), relative power loss (RPL), relative power generation (RPG), fill factor (FF) and the panel ML of the PV array configurations [79]. The uniqueness of this paper is that the performance assessment is carried out on various PV array configurations, including ladder structure along with the hybrid PV array configurations, which are not covered in any of the published papers so far.
The paper is organized as follows. Section 2 deals with the mathematical modeling of PV cell/module/array. Section 3 discusses the various shading patterns for the simulation. Section 4 presents the mathematical modeling of the HC PV array configuration under uneven row and column shading. Section 5 investigates the simulation results of various PV array configurations under and uniform irradiance and PSCs. Section 5 also discusses the performance of PV array configurations under dynamic shading conditions. Section 6 discusses the performance assessment of different PV array topologies, and Section 7 concludes the paper.

2. Mathematical Modeling of the PV Cell/Module/Arrays

The researchers require a reliable, feasible and flexible PV model to precisely forecast the power generated by PV cells when connected in series/parallel combinations. This section of the paper discusses a single diode PV model for the cell, and finally, it can be extended to the PV module and array. To model the PV cell/module/array, the various parameters are taken from the manufacturer’s datasheet.

2.1. Modeling of a Single PV Cell Based on a Single Diode Model

The equivalent circuit of the single diode PV cell model comprises of a single current source with one anti-parallel diode, series resistance and shunt resistance [80,81,82,83,84,85,86,87]. The equivalent model of the single PV cell is shown in Figure 3.
Apply Kirchhoff’s current law for the PV cell model shown in Figure 3. The PV cell current is given in Equation (1).
I p v = I p h o t o I d i o d e I p
where Iphoto is the photocurrent when the PV cell is subjected to incident sunlight, this current is varying linearly depends on the solar irradiance at a specific temperature. The anti-parallel diode current is Idiode, and it is responsible for the non-linearity of the PV cell. Ip represents the shunt resistor current, and substitute the expression for Ip and Idiode in Equation (1). Therefore, the cell current is derived as per Equation (2).
I p v = I p h o t o I 0 ( e x p ( q ( V + I p v R s e ) a k T ) 1 ) ( V + I p v R s e R p )
where q is the electron charge, and its value is 1.602 × 10−19 C, a is the diode ideality factor, Boltzmann constant represented as k = 1.3806503 × 10−23 J/K, Io is the saturation current of the diode, T represents the cell temperature and Rp and Rse represent the shunt and series resistance, respectively.

2.2. Modeling of a Single PV Module Based on the Single Diode Model

The PV module is made up of series-connected PV cells, and several series-connected PV cells are represented as Nse. For example, the SPR-200-BLK-U PV module (SunPower, CA, USA) consists of 72 PV cells, and SPR-76R-BLK-U panel (SunPower, CA, USA) consists of 24 series-connected PV cells. The output current (Ipv, P) of the PV module in terms of the output voltage (VP) when Nse cells are connected in series. The total PV module current is represented in Equation (3).
I p v , P = I p h o t o I 0 ( e x p ( q ( V P + I p v , P R s e ) N s e a k T ) 1 ) ( V P + I p v , P R s e N s e N s e R p )
Equation (3) can be extended to any number of series-connected PV cells, and it applies to any of the PV modules. It is not restricted to a single panel. If there are several series-connected panels (Nmo), and there are several series-connected PV cells in each panel (Nser), then Nse can be rewritten as per Equation (4).
N s e = N m o × N s e r

2.3. Modeling of a PV Array Based on the Single Diode Model

In the PV array, the PV panels are connected in series and parallel combinations. To start with the single PV cell, several PV cells connected in series to derive the PV module and several modules connected in series to obtain PV string and several strings attached in parallel to form PV array [76]. The equivalent circuit of the PV array is shown in Figure 4. Ns represent the series-connected panels, and Np represents the parallel-connected PV strings. The output current (Iar) of PV array in terms of output voltage (Var) is presented in Equation (5).
I a r = N p I p h o t o N p I 0 ( e x p ( q ( V a r + I a r N s N p R s e ) N s a k T ) 1 ) ( V a r + I a r R s e N s N p N s N p R p )
The modeling of the PV array in MATLAB/Simulink is done by using Equation (5). With the help of the following assumptions, such as N p I p h o t o = I p h o t o N p I o = I o , ( N s / N p ) R s e = R s e , and ( N s / N p ) R p = R p Equation (5) is modified as Equation (6).
I a r = I p h o t o I o ( e x p ( q ( V a r + I a r R s e ) N s a k T ) 1 ) ( V a r + I a r R s e R p )
With the assumptions, Equation (6) is similar to the V–I relation for a single PV cell and, it is proved that the PV array equivalent circuit is similar to the PV cell equivalent circuit. However, the variables in Figure 3 and the variables in Equation (6) have different meanings based on the above assumptions. The various parameters of the SPR-200-BLK-U PV module are used for modeling and simulating PV array topologies using MATLAB/Simulink and presented in Table 1.

3. Effects and Various Shading Patterns under Partial Shading Conditions

3.1. Effects of PSC on PV Arrays

The PSCs of the conventional SP array configuration is considered as reference, and it generates panel MLs during various shading patterns. The magnitude of the MLs varies with the PV array operating point. During shading conditions, the PV module voltage is too less, and by-pass diodes short-circuit the panel to maintain the regular operation throughout the string and prevents the module from the hot spots. In most cases, the PV panels provided with two bypass diodes to reduce the power loss, as discussed in [88,89,90,91,92]. The panel mismatching can be noticed from the P–V characteristic, and the characteristics have multiple peaks. The P–V characteristic curve has multiple local peaks and one global peak, which misleads the MPPT algorithms. The main reasons for altering the PV panel interconnections are as follows. (i) The rise in maximum output power and (ii) multiple peak shedding. Alternative topologies have a smaller number of LPs when compared to the conventional SP configuration. Throughout the PV array, the impacts of degraded PV modules on standard operating PV panels are reduced by an extra redundancy in the circuit.

3.2. Shading Patterns

The different shading patterns under PSCs on various PV array topologies such as SP, HC, BL, TCT, LD, BLHC, BLTCT and SPTCT is described in this section of the paper. Overall, the shading patterns are grouped into two parts. Group 1, called static shading pattern, consists of four shading patterns, such as uneven row shading (URS), uneven column shading (UCS), diagonal shading (DS) and uneven corner shading pattern (UCRS). Group 2, called dynamic shading pattern, consists of two shading patterns, such as random shading-I (R-I) and random shading-II (R-II). Group 2 shading patterns are based on several shaded panels per PV string and several PV strings randomly at any time. The solar irradiance and the shading patterns on each PV panel under PSCs are shown in Figure 5 for HC PV array configuration, and the same has been applicable for other PV array configurations.
Figure 5a–f illustrates the shading patterns to be adopted in the analysis of the eight PV array configurations, as shown in Figure 2. The characteristics of PV array topologies under each shading pattern was simulated and explained in Section 5.

4. Mathematical Analysis of HC PV Array Configuration under PSCs

In HC PV array configuration, the diagonal PV modules are connected, as shown in Figure 2c. The HC PV array configuration is a modified version of the BL PV array configuration, which includes the advantages of both the TCT and BL configurations. The HC configuration is a tradeoff between TCT and BL topologies, and the main difference between the TCT and HC configuration is that the HC configuration has half of the interconnections of the TCT array configuration. However, the BL configuration has a smaller number of interconnections than the HC configurations. Moreover, all the panels in the PV array behave identically, and the output power of the PV array is similar for all the topologies when there is no module mismatch. When there is a module mismatch, one of the solar PV array topologies performance was better than the others. The performance of the HC array configuration is comparable to TCT and hybrid topologies and better than the conventional BL, LD, S, P and SP configurations. To achieve the broad investigation of HC PV array configuration under PSCs, the mathematical analysis is required under normal operating conditions and then extended to different operating conditions. So, the most preferred 4 × 4 sized HC structure is considered as shown in Figure 6a for the mathematical analysis under normal operating conditions and analyzed at uneven row shading and uneven column shading, as shown in Figure 6b,c. The concept can be extended to all shading patterns. The module mismatch is caused by irregular solar irradiation received by each cell/module. From the equivalent circuit of the PV cell, as shown in Figure 3, the photocurrent, Iphoto(G), is directly proportional to the solar irradiance, and it is presented in Equation (7).
I p h o t o ( G ) = G G o I p o
where, Ipo is the photocurrent generated at Go (= 1000 W/m2). The V–I relationship of the cell fulfills the following function.
f ( I , V , G ) = I p h o t o ( G ) + I d i o d e ( V + I p v R s e ) V + I p v R s e R p I = 0
where, Idiode represents the diode current. When analyzing the PV array, one may start with writing the expressions governing the V–I relationships of the 16 PV modules. Apply Kirchhoff’s current and voltage laws to nodes and loops to derive the equations for the respective PV array configuration. Figure 6a shows the HC array configuration, which is more accessible than the SP, TCT, BL, LD and other hybrid topologies. The V–I relationships of the 16 modules can be given by:
f ( I m , V n , G i ) = 0 , i = 1 , 2 , 3 , , 16
where, subscript ‘m’ represents the current, ‘n’ represents the voltage and ‘i’ represents the PV module number, which are given by the below equations.
m = { 1 , for   i = 1 2 , for   i = 2 , 3 3 , for   i = 4 i 1 ,   for   5     i 12 12 , for   i = 13 13 , for   i = 14 , 15 14 , for   i = 16
n = { 1 , for   1     i   4 5 , for   i = 6 6 , for   i = 7 7 , for   i = 10 8 , for   i = 11 i , for   13     i   16
It is observed that there are 12 voltages and 14 currents as variables, and hence 26 equations are required. In the HC configuration, five nodes are indicated in Figure 6a. For node numbers 1 and 4 the Kirchhoff’s current law is applied, and the equations are written as:
I 1 + I 4 = I 2 + I 5
I 3 + I 7 = I 2 + I 6
Similarly, for the node number at 3, the equation can be written as:
I 6 + I 10 = I 5 + I 9
Similarly, for node numbers 2 and 5, the equation can be written as:
I 9 + I 13 = I 12 + I 8
I 11 + I 14 = I 13 + I 10
For each loop, the Kirchhoff’s voltage law is applied, and the equations are given as,
V 1 = V 5 ; V 4 = V 8
V 2 + V 3 = V 6 + V 7
V 14 + V 15 = V 10 + V 11
V 9 = V 13 ; V 12 = V 16
V 6 + V 7 = V 10 + V 11
Finally, apply Kirchhoff’s voltage law for the loop containing the four modules in the first column, and the output voltage is given by,
n = 1 4 V n = V o u t
The schematic of Figure 6a contains 14 currents and 12 voltages, summing up to 26 unknown variables. Equation (9) gives 16 V–I relationship Equations, Equations (12)–(16) gives five current Equations, and Equations (17)–(21) gives five voltage equations, summing up a total of 26 equations, which is equal to the number of unknown variables. Equations (10)–(22) can be applied for the HC array configuration under normal operating conditions. This concept can be extended to different operating conditions.
Based on the above discussions and by considering Figure 6b,c, it is concluded that the sum of node currents at different nodes and the voltage of parallel modules are equal. The expressions for the node voltage, total current, and voltage of the array is given in Equations (23)–(25), respectively.
V 1 = V 5 ; V 9 = V 13 ; V 4 = V 8 ; V 12 = V 16 ; V 2 + V 3 = V 6 + V 7 ; V 6 + V 7 = V 10 + V 11 = V 14 + V 15
I o u t = I 1 + I 5 + I 9 + I 13
V o u t = V 13 + V 14 + V 15 + V 16 = V 1 + V 2 + V 3 + V 4
The PV modules are shaded by term α for the three-shading pattern of HC configurations, as shown in Figure 6b,c. The shading factor, α, is given in Equation (26).
α = 1 G G o
where Go is the incoming solar irradiance, and G is the solar irradiance after shading. The panel currents from I1–I16 are obtained from Equation (3). For unshaded PV panels, the photocurrent, Iphoto is defined as follows.
I s c = G o 1000 × I p h o t o
where, Isc is the short circuit current of the PV module, and for the shaded module, the photocurrent is defined as follows.
I s c = ( 1 α ) G o 1000 × I p h o t o

4.1. Case-I: Uneven Row Shading

As presented in Figure 6b, the modules in the first row are shaded unevenly, and the expressions for the currents can be derived and given in Equations (29)–(33).
I 2 = I 3 = I 4 = I 6 = I 7 = I 8 = I 10 = I 11 = I 12 = I 14 = I 15 = I 16
I 16 = I p h o t o I 0 ( e x p ( q ( V P U + I p v , P R s e ) N s e a k T ) 1 ) ( V P U + I p v , P R s e N s e N s e R p )
V P U = V 2 , 3 , 4 , 6 , 7 , 8 , 10 , 11 , 12 , 14 , 15 , 16
I 1 = I 5 = I 9 = I 13 = I p h o t o I p h o t o α G 1000 I 0 ( e x p ( q ( V P S + I p v , P R s e ) N s e a k T ) 1 ) ( V P S + I p v , P R s e N s e N s e R p )
V P S = V 1 , 5 , 9 , 13
Substitute Equations (29)–(33) in Equations (24)–(25), the V–I relation can be developed as follows:
I o u t = 4 I p h o t o I p h o t o α G 1000 4 I 0 ( e x p ( q ( V P S + I p v , P R s e ) N s e a k T ) 1 ) 4 ( V P S + I p v , P R s e N s e N s e R p )
By considering Equation (25), substitute the expression for VPS in Equation (34), and the expression is as follows:
I o u t = 4 I p h o t o I p h o t o α G 1000 4 I 0 ( e x p ( q ( V P S 1 + I p v , P R s e ) N s e a k T ) 1 ) 4 ( V P S 1 + I p v , P R s e N s e N s e R p )
V P S 1 = V o u t ( V 2 + V 3 ) V 4
From Equations (24)–(25), the expressions for the node voltage are given below.
V 4 = N s e a K T [ ln ( I p h o t o I o u t 4 I p v , P R s e R p ) ] q I p v , P R s e q
V 2 + V 3 = 2 N s e a K T [ ln ( I p h o t o I o u t 4 I p v , P R s e R p ) ] 2 q I p v , P R s e q

4.2. Case-II: Uneven Column Shading

As presented in Figure 6c, the modules in the first column are shaded unevenly, and the expressions for the currents can be derived and given in Equations (39)–(46).
I 5 = I 6 = I 7 = I 8 = I 9 = I 10 = I 11 = I 12 = I 13 = I 14 = I 15 = I 16
I 16 = I p h o t o I 0 ( e x p ( q ( V P U + I p v , P R s e ) N s e a k T ) 1 ) ( V P U + I p v , P R s e N s e N s e R p )
V P U = V 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16
I 1 = I 2 = I 3 = I 4 = I p h o t o I p h o t o α G 1000 I 0 ( e x p ( q ( V P S + I p v , P R s e ) N s e a k T ) 1 ) ( V P S + I p v , P R s e N s e N s e R p )
V P S = V 1 , 2 , 3 , 4
Substitute Equations (29)–(33) in Equations (24)–(25), the V–I relation can be developed as follows:
I o u t = 4 I p h o t o I p h o t o α G 1000 4 I 0 ( e x p ( q ( V P S + I p v , P R s e ) N s e a k T ) 1 ) 4 ( V P S + I p v , P R s e N s e N s e R p )
Substitute Equation (30) and Equation (32) in Equations (4)–(5), the relation can be developed as follows:
4 I p h o t o I p h o t o α G 1000 4 I 0 ( e x p ( q ( V 5 , 6 , 7 , 8 + I p v , P R s e ) N s e a k T ) 1 ) 4 ( V 5 , 6 , 7 , 8 + I p v , P R s e N s e N s e R p ) = 4 I p h o t o I p h o t o α G 1000 4 I 0 ( e x p ( q ( V 9 , 10 , 11 , 12 + I p v , P R s e ) N s e a k T ) 1 ) 4 ( V 9 , 10 , 11 , 12 + I p v , P R s e N s e N s e R p ) = 4 I p h o t o I p h o t o α G 1000 4 I 0 ( e x p ( q ( V 13 , 14 , 15 , 16 + I p v , P R s e ) N s e a k T ) 1 ) 4 ( V 13 , 14 , 15 , 16 + I p v , P R s e N s e N s e R p ) =
The output voltage of the array is obtained from Equation (42), Equation (25), and it can be expressed as follows:
V o u t = 4 V 5
By using Equation (46) and Equation (25), the output current of the array for the case-II can be developed as follows:
I o u t = 4 I p h o t o I p h o t o α G 1000 4 I 0 ( e x p ( q ( V o u t 4 + I p v , P R s e ) N s e a k T ) 1 ) 4 ( ( V o u t 4 ) + I p v , P R s e N s e N s e R p )

4.3. Mathematical Analysis during Two Shading Cases

In Section 4.1 and Section 4.2, the mathematical modeling of HC PV array configuration was discussed. The study of numerical analysis was discussed in this subsection. The investigation was as follows.
  • By examining case-1, it was concluded that (i) during the shaded situations, compared to the unshaded case, the value of Isc did not change, i.e., the current was almost constant, (ii) due to the ln relation in Equation (35), I–V characteristics of the HC PV array had two peaks. The point at which the I–V characteristics changed (In) its path could be given by 4 I p h o t o I p h o t o × ( α G / 1000 ) .
  • By examining case-2, it was concluded that (i) during the shaded situations, the Isc was changed compared to unshaded condition (i.e., Isc was equal to 4 I p h o t o I p h o t o × ( α G / 1000 ) , (ii) I–V characteristics of the HC PV array had three peaks, and it did not change its directions.
In is the current at which the I–V characteristics change its path due to the shading. Reaching this current (In) causes I–V characteristics to produce a new peak, and the breaking point current depends on the shading factor (α). The results of the mathematical analysis are presented in Table 2, and these values are obtained for Go = 1000 W/m2.

5. Simulation Results and Discussions

This section of the paper discussed the simulation of various 4 × 4 PV array topologies such as SP, HC, BL, TCT, LD, BLHC, BLTCT and SPTCT configurations. The MATLAB/Simulink software was used to compare various PV array configurations in terms of maximum output power under PSCs. For the simulation, 16 PV modules were used, and each PV module consisted of series-connected 72 PV cells. Each PV module was protected by the bypass diode, which was connected in anti-parallel with the module. Blocking diodes were connected to block the reverse flow of current. Assuming that the PV modules were operated at 25 °C temperature with different irradiance conditions, as presented in Figure 5.

5.1. SP PV Array Configuration

In the SP array configuration, four PV modules were connected in series to form a PV string to get the required output voltage, and then the strings (four PV strings) were connected in parallel to form the PV array getting the desired output current. This SP array configuration is commonly employed due to its economical operation and ease of connection. The array output current is the sum of individual PV string current in an array, and the array output voltage is the sum of the individual module voltage in a string. Along with bypass diode, the blocking diode was connected with the individual PV string to protect the string from the short circuit during PSCs. Under PSCs, the blocking diodes stop the backflow of the current into other string due to the voltage difference between the PV strings. In standalone systems, the blocking diodes block the reverse current from the battery storage unit to PV array at night time or under partial shading condition. The simulation results of PV array output characteristics such as I–V and P–V under the different shading patterns are presented in Figure 7. Due to the series connection in a string, the ML was more but less than the series and parallel PV array configurations.

5.2. TCT PV Array Configuration

This PV configuration can overcome the drawbacks of the SP PV array configuration. In this TCT configuration, first, all the PV modules in a row were connected in parallel, and then all the rows were series-connected. In this TCT PV array configuration, the voltage across each module in a row was equal to the Voc of the individual PV panel, and the PV array or required output voltage was equal to the sum of row voltages. The output current of the array is the sum of current produced from the PV panels in a row. The TCT PV array configuration utilizes a higher number of electrical wiring than the other PV array configurations. The higher number of electrical wiring made the system complex, increased the cost of the system and produced high power losses. The simulation results of TCT PV array output characteristics such as I–V and P–V under the different shading patterns are depicted in Figure 8.

5.3. BL PV Array Configuration

If a few cells in the PV module or a few PV modules in an array are subjected to PSCs, the output voltage of the whole system is reduced drastically. The SP PV array configuration consists of more series-connected modules in a string, and hence, the PV system produces more ML. To reduce the power losses in SP and S configurations, all the panels are connected in the bridge rectifier structure, as shown in Figure 2d, and this structure generally referred to as BL PV array configuration. The BL configuration consists of a more series connection than the TCT configuration and less than the S and SP configurations. So, the ML is higher than the TCT and lower than the S and SP configurations. From the structure, it can be seen that two modules in a bridge are connected in series and then connected in parallel. All the bridge structures are tied to get the required output voltage and output current. The simulation results of BL PV array characteristics such as I–V and P–V under the different shading patterns are presented in Figure 9.

5.4. HC PV Array Configuration

The drawbacks of the S, P, SP, BL and LD configurations can be overcome by considering HC PV array configuration. In this HC PV array configuration, the PV modules are a connected like hexagon of the honeycomb structure. The HC PV array configuration consists of a high number of series-connected PV modules than the TCT and BL and less than the S and SP PV array configuration. Therefore, the ML of HC PV array configuration was higher than the TCT, BLHC and BLTCT PV array configurations and less than the SPTCT, BL, SP and S PV array configurations. The simulation results of HC PV array output characteristics such as I–V and P–V under the different shading patterns are presented in Figure 10.

5.5. LD PV Array Configuration

This LD PV configuration can overcome the drawbacks of the BL and SP PV array configuration. In this LD configuration, the PV modules in a row of the first two columns were connected in parallel, and then the rows were series-connected. The structure of the LD configuration looks like a ladder. In LD PV array configuration, the voltage across each module in a row is equal to the Voc of the individual PV panel. The output current of the array is the sum of current produced from the PV panels in a row. The structure of the LD is not having any series connected panels; however, the rows are connected in series. So, the ML is less than the BL, and SP and higher than the TCT, HC and other hybrid configurations. The simulation results of LD PV array output characteristics such as I–V and P–V under the different shading patterns are presented in Figure 11.

5.6. BLHC PV Array Configuration

This BLHC PV configuration can overcome the drawbacks of the BL, HC, LD and SP PV array configuration. In BLHC configuration, the PV modules were connected as similar to the TCT configuration except for the first-row modules. The BLHC configuration can overcome the drawback of the conventional BL and HC configurations, i.e., a smaller number of series-connected panels. The PV modules are tied together to get the desired output voltage. The number of series-connected PV modules is less than the HC, LD, BL and SP configurations. So, the ML is very less than the HC, BL, LD, SP, BLTCT, SPTCT and slightly higher than the TCT configuration. The simulation results of BLHC PV array output characteristics such as I–V and P–V under the different shading patterns are presented in Figure 12.

5.7. BLTCT PV Array Configuration

This BLTCT PV configuration can overcome the drawbacks of the conventional array configurations except for the TCT configuration. In the BLTCT configuration, the PV modules were connected in a similar fashion as the BL configuration except for the middle row modules in which the modules were tightly tied. The BLTCT configuration can overcome the drawback of the conventional BL and TCT configurations, i.e., a smaller number of the series-connected panels, and a smaller number of electrical wirings. The number of series-connected PV modules was less than the HC, LD, BL and SP configurations, but higher than the TCT and BLHC configurations. So, the ML was lesser than the HC, BL, LD, SP and SPTCT, and higher than the BLHC and TCT configurations. The simulation results of BLTCT PV array output characteristics such as I–V and P–V under the different shading patterns are presented in Figure 13.

5.8. SPTCT PV Array Configuration

The SPTCT PV configuration can overcome the drawbacks of the conventional array configurations except for the HC and TCT configurations. In SPTCT configuration, the PV modules were connected in a similar fashion as the SP configuration except for the middle row modules in which the modules were tightly tied. The SPTCT array configuration had a higher number of series-connected modules as similar to the SP configuration, but less than the SP configuration combined with the benefits of TCT configuration. The SPTCT configuration can overcome the drawback of the conventional SP and TCT configurations, i.e., a smaller number of series-connected panels, and a smaller number of electrical wirings. The number of series-connected PV modules is less than the SP configurations but higher than the other configurations. So, the ML is lesser than the BL, LD and SP, and higher than the HC, BLHC, BLTCT and TCT configurations. The simulation results of SPTCT PV array output characteristics such as I–V and P–V under the different shading patterns are presented in Figure 14.
The expressions for output array output voltage, array output current and array output power of various PV array configurations in terms of module/string voltage/current are listed in Table 3.

6. Performance Evaluation of Various PV Array Configurations under PSCs

This section of the paper discussed the various comparisons of evaluation parameters of different PV array topologies such as SP, TCT, BL, HC, LD, BLHC, BLTCT and the SPTCT configuration under the operating conditions such as uniform irradiance and PSCs to choose the excellent array configuration that delivers high performance. The assessment was carried out by calculating the theoretical power generations under different operating conditions, the number of LPs, fill factor (FF) and mismatching loss. The ML is represented as ΔPL, and it was calculated as a percentage. The expression for ΔPL in a percentage is given in Equation (48). The theoretical power generation was calculated as per Equation (49).
M L ,   Δ P L = P m p P P S C P m p × 100
where, the maximum power generation under the uniform irradiance condition is represented by Pmp, and the power generation at certain PSC is represented by PPSC. PPSC can be calculated by multiplying Vmp and Imp of GP at the respective PSC. The theoretical power generation in watts can be calculated by using Equation (49) in which G is solar irradiance under PSC of the individual module, Go is solar irradiance under uniform irradiance and i is the total number of PV modules.
P t h e = i = 1 i = 16 ( G G o × P m p , i )
Theoretical power generation (Pthe) can be useful for calculating the relative power loss of the respective PV array configuration. The relative power loss (RPL) in watts of the solar PV array can be calculated by using Equation (50). The relative power gained (RPG) in percentage concerning the maximum output power of SP PV array can be calculated by using Equation (51).
R P L = P t h e P m p   ( at   GP )
R P G = P m p , i P m p , S P P m p , S P × 100
where the term ‘i’ represent the various PV array topologies such as TCT, BL, HC, LD, BLHC, BLTCT and SPTCT, and Pmp,SP represents the PV array output power of SP configuration. Another vital assessment parameter of the solar PV system is FF. If FF is near unity, then the performance of the solar PV system is higher. The FF can be calculated by using Equation (52).
F F = ( V m p I m p )   at   respective   PSC V o c * I s c × 100
At first, the performance assessment of the solar PV topologies could be carried out, and then, the same was extended to other shading patterns, as shown in Figure 5. For all the assessment, the temperature was kept constant at 25 °C.

6.1. Standard Test Conditions (STCs)

In general, the standard test condition (STC) of the PV module is given by the manufacturer. The temperature at STC was 25 °C, and the solar irradiance at STC was 1000 W/m2. From the simulation results, as shown in Figure 7, Figure 8, Figure 9, Figure 10, Figure 11 and Figure 12, various configurations such as SP, TCT, BL, HC, LD, BLHC, BLTCT and SPTCT produced the maximum array output power of 3200 W with single LP, which is referred to as GP. The voltages and currents at OC, SC, GP and LPs are listed in Table 4 for STCs. During STCs, all the topologies produce almost the same voltage and current at GP. The ML was nearly zero, and FF was roughly equal to 77.3% for all the topologies.

6.2. URS Pattern

For this assessment, the solar irradiance of the first-row modules is changed as per Figure 5a. The various performance parameters are listed in Table 5 for all array configurations. Under the URS pattern, all the configurations exhibited single LP and one GP. All the configurations found GP at 2384 W. The ML of all the configurations was almost equal to 25.5% with the FF varying between 57.89 and 58.08%. From the simulation results and the above discussions, it can be observed that BLHC was the better option in terms of FF, and TCT was the better option in terms of ML. However, the performance of both BLHC and TCT configurations were similar. Therefore, the researcher could select a better configuration based on the electrical wiring connections.

6.3. UCS Pattern

For this assessment, the solar irradiance of the first column modules was changed as per Figure 5b. The various performance parameters are listed in Table 6 for all array configurations. Under UCS pattern, the TCT produced two LPs at 2219 W; 1483 W and single GP at 163.2 V; 17.53 A; 2859 W. The ML was equal to 10.65% with FF equal to 71.48%, which was highest among all the array topologies. In addition, the configurations such as HC and BLHC also exhibited two LPs, the FF of both the configurations were greater than 70%, and MLs of both configurations were 1% higher than the TCT configuration. All the hybrid configurations had better values of FF and comparable values of % MLs but introduced three LPs, which misled the MPPT algorithms. Therefore, in all the aspects, the configurations such as TCT and BLHC exhibited better performance during the UCS pattern.

6.4. UCRS Pattern

For this assessment, the solar irradiance of the four corner modules were changed as per Figure 5c. The various performance parameters are listed in Table 7 for all array configurations. All the topologies produced two LPs and a single GP. Under the UCRS pattern, the TCT produced LPs at 1568 W; 2246 W and single GP at 165.7 V; 16.75 A; 2748 W. The ML was equal to 14.13% with FF equal to 67.48%, which was highest among all the array topologies. The hybrid BLHC and BLTCT array configuration exhibited LPs at 1568 W; 2259 W, and 2253 W; 1585 W, respectively, and single GP at 2738 W with 14.44% ML and 66.40% FF. The maximum power generation was just 10 W less than the TCT configuration but it was better than the SP, BL, LD and SPTCT configurations. Moreover, the HC exhibited GP at 2734 W, which was better than the other topologies except for TCT, BLTCT and BLHC with decent ML (14.56%) and FF (66.49%), which was comparable to hybrid topologies. From the simulation results from Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12, Figure 13 and Figure 14, the TCT configuration increased the GP to +4.84%, +2.46%, +0.51%, +1.25%, +0.36%, +0.36% and +2.15% when compared to SP, TCT, BL, HC, LD, BLHC, BLTCT and SPTCT, respectively. Here, ‘+’ sign indicates power gain.

6.5. DS Pattern

For this assessment, the solar irradiance of the first diagonal modules was changed as per Figure 5d. The various performance parameters are listed in Table 8 for all array configurations. The topologies such as SP and BL produced one LP, and other topologies produced two LPs. Under the UCRS pattern, the TCT produced LPs at 2192 W; 718.6 W, and GP at 162.8 V; 17.51 A; 2851 W. The ML was equal to 10.90% with FF equal to 71.18%, which was highest among all the array topologies. The hybrid BLHC array configuration exhibited LPs at 755.2 W; 2198 W and GP at 2849 W with 10.97%, ML and 70.87%, FF. The maximum power generation was just 2 W less than the TCT configuration, but it was better than other configurations. The BLTCT exhibited GP at 2833 W, which was better than the other topologies except for TCT and BLHC with an ML equal to 11.47%, and FF equal to 70.50%. The ML and FF of SP, SPTCT, LD and BL topologies were poor, which was almost equal to 25.5%; 57.87%, 20.59%; 61.83%, 16.88%; 64.54% and 16.88%; 64.54%, respectively. From the simulation results from Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12, Figure 13 and Figure 14, the TCT configuration increased the power generation to +19.58%, +19.58%, +1.27%, +7.18%, +17.22%, +0.071%, +0.63% and +1.22% when compared to SP, BL, HC, LD, BLHC, BLTCT and SPTCT, respectively.

6.6. R-I Pattern

For this assessment, the solar irradiance of the random modules was changed as per Figure 5e. The various performance parameters are listed in Table 9 for all array configurations. The topologies such as TCT, BLHC and LD produced two LPs, and other topologies produced three LPs. Under R-I pattern, the TCT produces LPs at 714.7 W; 1926 W and GP at 165.1 V; 14.50 A; 2394 W. The ML was equal to 25.18% with FF equal to 61.59%, which was highest among all the array topologies. The hybrid BLHC configuration exhibited LPs at 731 W; 1910 W, and GP at 2389 W with 25.34%, ML, and 61.30%, FF. The maximum power generation was 5 W less than the TCT configuration and better than other topologies. The BL exhibited GP at 2352 W, which was better than the other topologies except for TCT and BLHC with ML equal to 26.50% and FF equal to 60.30%. From the simulation results from Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12, Figure 13 and Figure 14, the TCT configuration increased the power generation to +9.96%, +1.78%, +7.11%, +9.46%, +0.2%, +3.81% and +4.17% when compared to SP, BL, HC, LD, BLHC, BLTCT and SPTCT, respectively.

6.7. R-II Pattern

For this assessment, the solar irradiance of the random modules was changed as per Figure 5f. The various performance parameters are listed in Table 10 for all array configurations. Except for TCT and BLHC configuration, other topologies such as SP, BL, HC, LD, BLTCT and SPTCT produced three LPs. Under the R-II pattern, the TCT produced LPs at 750.6 W; 1458 W and GP at 167 V; 11.77 A; 1966 W. The ML was equal to 38.56% with FF equal to 48.11%, which was highest among all the array topologies. The BLHC array configuration exhibited LPs at 751.7 W; 1458 W, and GP at 1966 W with 38.56%, ML, and 47.99%, FF. From the simulation results from Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12, Figure 13 and Figure 14, the TCT configuration increased the power generation to +10.01%, +12.72%, +2.66%, +2.39%, 0%, +2.28% and +9.04% when compared to SP, BL, HC, LD, BLHC, BLTCT and SPTCT, respectively.

6.8. RPL and RPG Comparison

Section 6.1, Section 6.2, Section 6.3, Section 6.4, Section 6.5, Section 6.6, and Section 6.7,. discuss the performance parameters of various PV array topologies under different shading patterns. For a better understanding of the readers, this section discussed the comparison of various array topologies based on the RPL and RPG. The comparison table is given in Table 11 and Table 12. Figure 15 shows the maximum power generation of all the topologies under various shading patterns. Figure 16 and Figure 17 show a comparison between various PV array topologies under different shading patterns in terms of RPL and RPG.
The results obtained from the simulation results described the relationship between the PV array output power and the type of interconnection within the PV array. From Table 11 and Figure 16, the PV array topologies were ordered in ascending order in terms of RPL as follows: SP > BL > LD > SPTCT > HC > BLTCT > BLHC > TCT and from Table 12 and Figure 17, the PV array topologies were ordered in ascending order in terms of RPG as follows: SP < BL < LD < SPTCT < HC < BLTCT < BLHC < TCT. Besides, the simulation results concluded that the TCT array configuration was superior to other PV array topologies with the least power loss, 14%, and high-power gain, 19.51%. Moreover, the BLHC PV array configuration was performing better than the BL, SP, HC, LD, BLTCT and SPTCT, and the performance was competitive to TCT with less complexity in electrical wiring than the TCT configuration. So, the power loss of the PV system with the BLHC PV array configuration was less than the PV system with the TCT array configuration due to less electrical wiring and hence power loss.

7. Conclusions

This paper assessed the performance of the conventional and the hybrid topologies that affect the maximum power generation of the PV system under different shading patterns. Moreover, this paper discussed the mathematical analysis of the HC PV array topology, which is not covered in previous publications, and the expressions for the voltage and current were derived for UCS and URS patterns. The simulation was carried out to check the effectiveness of all the configurations under static and dynamic shading patterns. The PV array characteristics such as P–V and I–V characteristics were analyzed under various shading patterns, as discussed above. The performance of the array configurations was assessed based on the parameters such as Voc, Isc, GP, LPs, voltage and current of the individual GP and LPs, ML, RPG, RPL and FF. All the topologies were simulated with the bypass diode to maximize the power under PSCs. This paper discussed the reduction of MLs in the PV array using a bypass diode and stringing arrangement approaches. By using both methods, the PV array could generate the maximum output by mitigating the ML significantly. Under various shading patterns, the TCT configuration was superior in producing the maximum output power than the other topologies. However, this paper also reported that the hybrid BLHC topology could perform as similar to TCT, and the performance was comparable to TCT in terms of electrical wiring complexity. From the results, it is noticed that both the BLHC and TCT topology was optimal when the modules were shaded in a single string. If the shading is spread across the strings, then BLHC is optimal topology. If shaded modules are spread across half of the total strings, either SP or TCT or BLHC or HC may be optimal depending on the shading intensity. It is also observed that a greater number of series-connected modules increased the MLs. Based on this criterion, the descending order of the configuration was as follows: TCT, BLHC, BLTCT, HC, SPTCT, LD, BL and SP PV array configuration. An alternative configuration increased the output power by 1.2%, 1.8%, 3.2%, 3.4%, 3.3%, 3.1% and 2.8% for BL, LD, HC, TCT, BLHC, BLTCT and SPTCT topologies, respectively as compared to the SP configuration. Even though the alterations in PV array configuration seemed to be key to fighting against MLs, the estimation of an additional wiring and frequent maintenance of the PV plant should be addressed to establish the cost-effective alternative array configuration designs. The study on various PV array configurations may be tested and verified in the physical site by considering various shading factors and other experimental factors.

Author Contributions

M.P. was originally responsible for conceptualization, methodology, simulation and prepared the original draft of the article. U.S. verified the simulation data, draft writing, and also provided technical guidance. T.S.B. made a formal analysis of the technical write-up, and T.S.B. also collected the technical resources along with the formal editing of the paper. R.M.E. made formal analysis, investigated the simulation data and reviewed the overall content of the paper. R.M.E. and L.M.-P. have done an overall review, editing and supervision. All authors have read and agreed to the published version of the manuscript.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Acknowledgments

The authors extend their thankfulness to GMR Institute of Technology, Rajam, Andhra Pradesh, India, for providing facility and allowing us to validate the performance of the system at the laboratory. The authors also thank Renewable Energy Lab, Prince Sultan University, Saudi Arabia, for their extended support for technical guidance.

Conflicts of Interest

The authors declare no conflict of interest.

Nomenclature

List of Symbols
Ipv, Ipv,P and IarPV cell, PV module and PV array current in A, respectively
IphotoPhotocurrent in A
I0Diode saturation current in A
qElectron charge in C
V, VP, and VarPV cell, PV module and PV array voltage in V, respectively
Rse and RpSeries and shunt resistance of the PV cell in Ω, respectively
Nse and NsNumber of series connected PV cells and PV modules, respectively
NpNumber of parallel connected PV modules
aDiode ideality factor
kBoltzmann constant in J/K
TCell temperature in K
Voc and IscOpen circuit voltage in V and short circuit current in A of the PV module/array, respectively
Vmp and ImpMaximum power point voltage in V and current in A of the PV module/array, respectively
PmpPower at maximum power point in W of the PV module/array
IpoPhotocurrent of PV cell at standard solar irradiance, Go (1000 W/m2)
GActual solar irradiance during shading conditions in W/m2
Vn and ImVoltage in V and current in A of the respective PV module
Vout and IoutOutput voltage in V and Output current in A of the PV array, respectively
αShading factor
InCurrent at which the I–V characteristic change its path due to shade in A
PoOutput power of the PV array in W
ΔPLMismatching loss in W
PtheTheoretical power generation in W
PPSCPower generation at certain PSC in W
Pmp,iPower at MPP of various PV array topologies in W
Pmp,SPPower at MPP of SP PV array configuration in W
List of Abbreviations
PVPhotovoltaic
PSCPartial shading condition
SPSeries-Parallel
SSeries
HCHoney-Comb
TCTTotal-Cross-Tied
LDLadder
BLBridge-Linked
BLHCBridge-Linked Honey-Comb
BLTCTBridge-Linked Total-Cross-Tied
SPTCTSeries-Parallel Total-Cross-Tied
GPGlobal peak
LPLocal peak
FFFill factor
MLMismatching loss
MPPMaximum power point
MPPTMaximum power point tracking
URSUneven row shading
UCSUneven column shading
UCRSUneven corner shading
DS Diagonal shading
R-IRandom shading-I
R-IIRandom shading-II
RPLRelative power loss
RPG Relative power generation

References

  1. Elavarasan, R.M. Comprehensive review on India’s growth in renewable energy technologies in comparison with other prominent renewable energy-based countries. J. Sol. Energy Eng. 2020, 142, 030801. [Google Scholar] [CrossRef]
  2. Elavarasan, R.M.; Shafiullah, G.M.; Manoj Kumar, N.; Padmanaban, S. A state-of-the-art review on the drive of renewables in Gujarat, state of India: Present situation, barriers and future initiatives. Energies 2020, 13, 40. [Google Scholar] [CrossRef] [Green Version]
  3. Elavarasan, R.M.; Shafiullah, G.M.; Padmanaban, S.; Manoj Kumar, N.; Annapurna, A.; Ajayragavan Manavalanagar, V.; Mihet-Popa, L.; Holm-Nielsen, J.B. A comprehensive review on renewable energy development, challenges, and policies of leading Indian states with an international perspective. IEEE Access 2020, 8, 74432–74457. [Google Scholar] [CrossRef]
  4. El-Khozondar, H.J.; El-Khozondar, R.J.; Matter, K. A review study of photovoltaic array maximum power tracking algorithms. Renew. Wind Water Sol. 2016, 3, 3. [Google Scholar] [CrossRef] [Green Version]
  5. Mohapatra, A.; Nayak, B.; Das, P.; Barada Mohanty, K. A review on MPPT techniques of PV system under partial shading condition. Renew. Sustain. Energy Rev. 2017, 80, 854–867. [Google Scholar] [CrossRef]
  6. Elavarasan, R.M. The motivation for renewable energy and its comparison with other energy sources: A review. Eur. J. Sustain. Dev. Res. 2019, 3, em0076. [Google Scholar] [CrossRef]
  7. Bhatnagar, P.; Nema, R.K. Maximum power point tracking control techniques: State-of-the-art in photovoltaic applications. Renew. Sustain. Energy Rev. 2013, 23, 224–241. [Google Scholar] [CrossRef]
  8. Bana, S.; Saini, R.P. Experimental investigation on power output of different photovoltaic array configurations under uniform and partial shading scenarios. Energy 2017, 127, 438–453. [Google Scholar] [CrossRef]
  9. Belhachat, F.; Larbes, C. Modeling, analysis and comparison of solar photovoltaic array configurations under partial shading conditions. Sol. Energy 2015, 120, 399–418. [Google Scholar] [CrossRef]
  10. Premkumar, M.; Karthick, K.; Sowmya, R. A comparative study and analysis on conventional solar PV based DC-DC converters and mppt techniques. Ind. J. Electr. Eng. Comput. Sci. 2018, 11, 831–838. [Google Scholar]
  11. Premkumar, M.; Sumithira, T.R. Design and implementation of new topology for non-isolated dc-dc microconverter with effective clamping circuit. J. Circuits Syst. Comput. 2019, 28, 1950082. [Google Scholar] [CrossRef]
  12. Premkumar, M.; Sumithira, T.R. Humpback whale assisted hybrid maximum power point tracking algorithm for partially shaded solar photovoltaic systems. J. Power Electron. 2018, 18, 1805–1818. [Google Scholar]
  13. Rezk, H.; Eltamaly, A. A comprehensive comparison of different MPPT techniques for photovoltaic systems. Sol. Energy 2015, 112, 1–11. [Google Scholar] [CrossRef]
  14. Islam, H.; Mekhilef, S.; Shah, N.B.M.; Soon, T.K.; Seyedmahmousian, M.; Horan, B.; Stojcevsk, A. Performance evaluation of maximum power point tracking approaches and photovoltaic systems. Energy 2018, 11, 365. [Google Scholar] [CrossRef] [Green Version]
  15. Sudhakar Babu, T.; Sangeetha, K.; Rajasekar, N. Voltage band based improved particle swarm optimization technique for maximum power point tracking in solar photovoltaic system. J. Renew. Sustain. Energy 2016, 8, 013106. [Google Scholar] [CrossRef]
  16. Azharuddin, S.; Mohammed, M.; Vysakh, M.; Harshal Vilas, T.; Nishant, B.; Sudhakar Babu, T.; Muralidhar, K.; Don, P.; Basil, J.; Balasubramanian, K.; et al. A near accurate solar PV emulator using dSPACE controller for real-time control. Energy Proc. 2014, 61, 2640–2648. [Google Scholar] [CrossRef] [Green Version]
  17. Sangeetha, K.; Sudhakar Babu, T.; Rajasekar, N. Fireworks algorithm-based maximum power point tracking for uniform irradiation as well as under partial shading condition. In Artificial Intelligence and Evolutionary Computations in Engineering Systems; Dash, S.S., Chandra Babu Naidu, P., Bayindir, R., Das, S., Eds.; Springer: Berlin/Heidelberg, Germany, 2016; pp. 79–88. [Google Scholar]
  18. Yousri, D.; Sudhakar Babu, T.; Allam, D.; Ramachandaramurthy, V.K.; Etiba, M.B. A novel chaotic flower pollination algorithm for global maximum power point tracking for photovoltaic system under partial shading conditions. IEEE Access 2019, 7, 121432–121445. [Google Scholar] [CrossRef]
  19. Dalia, Y.; Sudhakar Babu, T.; Allam, D.; Ramachandaramurthy, V.K.; Beshr, E.; Eteiba, M. Fractional chaos maps with flower pollination algorithm for partial shading mitigation of photovoltaic systems. Energies 2019, 12, 3548. [Google Scholar]
  20. Premkumar, M.; Mohamed Ibrahim, A.; Mohan Kumar, R.; Sowmya, R. Analysis and simulation of bio-inspired intelligent salp swarm MPPT method for the PV systems under partial shaded conditions. Inter. J. Comput. Digit. Syst. 2019, 8, 489–496. [Google Scholar]
  21. Manganiello, P.; Ballato, M.; Vitelli, M. A survey on mismatching and aging of PV modules: The closed-loop. IEEE Trans. Ind. Electron. 2015, 62, 7276–7286. [Google Scholar] [CrossRef]
  22. Gow, J.A. Development of a model for photovoltaic arrays suitable for use in simulation studies of solar energy conversion systems. In Proceedings of the 6th International Conference on Power Electronics and Variable Speed Drives, Nottingham, UK, 23–25 September 1996; pp. 69–74. [Google Scholar]
  23. Di Vincenzo, M.C.; Infield, D. Detailed PV array model for non-uniform irradiance and its validation against experimental data. Sol. Energy 2013, 97, 314–331. [Google Scholar] [CrossRef]
  24. Yousri, D.; Dalia, A.; Eteiba, M.B. Optimal photovoltaic array reconfiguration for alleviating the partial shading influence based on a modified harris hawks optimizer. Ener. Conv. Mana. 2020, 206, 112470. [Google Scholar] [CrossRef]
  25. Bingo, O.; Ozkaya, B. Analysis and comparison of different PV array configurations under partial shading conditions. Sol. Energy 2018, 160, 336–343. [Google Scholar] [CrossRef]
  26. Picault, D.; Raison, B.; Bacha, S.; Aguilera, J.; De La Casa, J. Changing photovoltaic array interconnections to reduce mismatch losses: A case study. In Proceedings of the 2010 9th International Conference on Environment and Electrical Engineering, Prague, Czech Republic, 16–19 May 2010; pp. 37–40. [Google Scholar]
  27. Maki, A.; Valkealahti, S. Power losses in long string and parallel-connected short strings of series-connected silicon-based photovoltaic modules due to partial shading conditions. IEEE Trans. Energy Conv. 2012, 27, 173–183. [Google Scholar] [CrossRef]
  28. Bizon, N. Global extremum seeking control of the power generated by a photovoltaic array under partially shaded conditions. Energy Conv. Manag. 2015, 109, 71–85. [Google Scholar] [CrossRef]
  29. Niazi, K.A.K.; Yang, Y.; Nasir, M.; Sera, D. Evaluation of Interconnection Configuration Schemes for PV Modules with Switched-Inductor Converters under Partial Shading Conditions. Energies 2019, 12, 2802. [Google Scholar] [CrossRef] [Green Version]
  30. Bidram, A.D.; Balog, S. Control and circuit techniques to mitigate partial shading effects in Photovoltaic arrays. IEEE J. Photovolt. 2012, 2, 532–546. [Google Scholar] [CrossRef]
  31. Nnamchi, S.N.; Oko, C.O.C.; Kamen, F.L.; Sanya, O.D. Mathematical analysis of interconnected photovoltaic arrays under different shading conditions. Cogent Eng. 2018, 5, 1507442. [Google Scholar] [CrossRef]
  32. Mohammadnejad, S.; Khalafi, A.; Morteza Ahmadi, S. Mathematical analysis of total-cross-tied photovoltaic array under partial shading condition and its comparison with other configurations. Sol. Energy 2016, 133, 501–511. [Google Scholar] [CrossRef]
  33. Wang, Y.J.; Hsu, P. Analysis of partially shaded PV modules using piecewise linear parallel branches model. World Acad. Sci. Eng. Tech. 2009, 60, 783–789. [Google Scholar]
  34. Teo, J.C.; Tan, R.H.; Ramachandaramurthy, V.K.; Tan, C. Impact of partial shading on the P–V characteristics and the maximum power of a photovoltaic string. Energies 2018, 11, 1860. [Google Scholar] [CrossRef] [Green Version]
  35. Wang, Y.J.; Hsu, P.C. An investigation on partial shading of PV modules with different connection configurations of PV cells. Energy 2011, 36, 3069–3078. [Google Scholar] [CrossRef]
  36. Yadav, A.S.; Pachauri, R.K.; Chauhan, Y.K. Comprehensive investigation of PV arrays with puzzle shade dispersion for improved performance. Sol. Energy 2016, 129, 256–285. [Google Scholar] [CrossRef]
  37. Yadav, A.S.; Pachauri, R.K.; Chauhan, Y.K.; Choudhury, S.; Singh, R. Performance enhancement of partially shaded PV array using novel shade dispersion effect on magic-square puzzle configuration. Sol. Energy 2017, 144, 780–797. [Google Scholar] [CrossRef]
  38. Ishaque, K.; Salam, Z.; Syafaruddin, A. A comprehensive MATLAB Simulink PV system simulator with partial shading capability based on two diode model. Sol. Energy 2011, 85, 2217–2222. [Google Scholar] [CrossRef]
  39. Qi, J.; Zhang, Y.; Chen, Y. Modeling and maximum power point tracking (MPPT) method for PV array under partial shade conditions. Renew. Energy 2014, 66, 337–345. [Google Scholar] [CrossRef]
  40. Karatepe, E.; Boztepe, M.; Colak, M. Development of a suitable model for characteristics photovoltaic arrays with shaded solar cells. Sol. Energy 2007, 81, 977–992. [Google Scholar] [CrossRef]
  41. Malathy, S.; Ramaprabha, R. Comparative analysis on the role of array size and configuration on energy yield of photovoltaic systems under shaded conditions. Renew. Sustain. Energy Rev. 2015, 49, 672–679. [Google Scholar] [CrossRef]
  42. Pareek, S.; Dahiya, R. Output power maximization of partially shaded 4*4 PV field by altering its topology. Energy Proc. 2014, 54, 116–126. [Google Scholar] [CrossRef] [Green Version]
  43. Patel, H.; Agarwal, V. MATLAB-based modeling to study the effects of partial shading on PV array characteristics. IEEE Trans. Energy Convers. 2008, 23, 302–310. [Google Scholar] [CrossRef]
  44. Kaushika, N.D.; Gautam, N.K. Energy yield simulations of interconnected solar PV arrays. IEEE Trans. Energy Convers. 2003, 18, 127–134. [Google Scholar] [CrossRef]
  45. Ramaprabha, R.; Mathur, B.L. A comprehensive review and analysis of solar photovoltaic array configurations under partial shaded conditions. Int. J. Photoenergy 2012, 2012, 120214. [Google Scholar] [CrossRef] [Green Version]
  46. Prince Winston, D.; Kumaravel, S.; Praveen Kumar, B.; Devakirubakaran, S. Performance improvement of solar PV array topologies during various partial shading conditions. Sol. Energy 2020, 196, 228–242. [Google Scholar] [CrossRef]
  47. Yadav, A.S.; Yadav, V.K.; Choudhary, S. Power enhancement from solar pv array topologies under partial shading condition. In Proceedings of the International Conference on Power Energy, Environment and Intelligent Control, Greater Noida, India, 13–14 April 2018; pp. 379–383. [Google Scholar]
  48. Kumar, K.; Vikas, G. A Comprehensive review on grid-tied solar photovoltaic system. J. Green Eng. 2017, 7, 213–254. [Google Scholar] [CrossRef]
  49. Sharip, M.R.M.; Haidar, A.M.A.; Jimel, A.C. Optimum configuration of solar PV topologies for dc microgrid connected to the longhouse communities in Sarawak, Malaysia. Int. J. Photoenergy 2019, 2019, 2657265. [Google Scholar] [CrossRef] [Green Version]
  50. Agrawal, N.; Avinashi, K. Power loss mitigation in partially shaded solar PV array through different interconnection topologies. AIP Conf. Proc. 2019, 2136, 040012. [Google Scholar]
  51. Amer Chaaban, M.; El Chaar, L.; Alahmad, M. An adaptive photovoltaic topology to overcome shading effect in PV systems. Int. J. Photoenergy 2015, 2015, 294872. [Google Scholar]
  52. Gonzalez Montoya, D.; David Bastidas-Rodriguez, J.; Adriana Trejos-Grisales, L.; Andres Ramos-Paja, C.; Petrone, G.; Spagnuolo, G. A procedure for modeling photovoltaic arrays under any configuration and shading conditions. Energies 2018, 11, 767. [Google Scholar] [CrossRef] [Green Version]
  53. Seyedmahmoudian, M.; Mekhilef, S.; Rahmani, R.; Yusof, R.; Renani, E.T. Analytical modeling of partially shaded photovoltaic systems. Energies 2013, 6, 128–144. [Google Scholar] [CrossRef] [Green Version]
  54. Petrone, G.; Ramos-Paja, C.A. Modeling of photovoltaic fields in mismatched conditions for energy yield evaluations. Electr. Power Syst. Res. 2011, 81, 1003–1013. [Google Scholar] [CrossRef]
  55. Kajihara, K.; Harakawa, T. Model of photovoltaic cell circuits under partial shading. In Proceedings of the IEEE International Conference on Industrial Technology, Taipei, China, 14–17 December 2005; pp. 866–870. [Google Scholar]
  56. Villalva, M.G.; Gazoli, J.R.; Filho, E.R. Comprehensive approach to modelling and simulation of photovoltaic arrays. IEEE Trans. Power Electron. 2009, 24, 1198–1208. [Google Scholar] [CrossRef]
  57. Gao, L.; Dougal, R.A.; Liu, S.; Iotova, A.P. Parallel-connected solar PV system to address partial and rapidly fluctuating shadow conditions. IEEE Trans. Ind. Electron. 2009, 56, 1548–1556. [Google Scholar]
  58. Babu, T.S.; Yousri, D.; Balasubramanium, K. Photovoltaic array reconfiguration system for maximizing the harvested power using population-based algorithms. IEEE Access 2020, 13, 1–15. [Google Scholar] [CrossRef]
  59. Rani, B. Enhanced power generation from PV array under partial shading conditions by shade dispersion using Su-Do-Ku configuration. IEEE Trans. Sustain. Energy 2013, 4, 594–601. [Google Scholar] [CrossRef]
  60. Horoufiany, M.; Ghandehari, R. Optimization of the Sudoku based reconfiguration technique for PV arrays power enhancement under mutual shading conditions. Sol. Energy 2018, 159, 1037–1046. [Google Scholar] [CrossRef]
  61. Romano, P.; Candela, R.; Cardinale, M.; Li Vigni, V.; Musso, D.; Sanseverino, E.R. Optimization of photovoltaic energy production through an efficient switching matrix. J. Sustain. Dev. Energy Water Environ. Syst. 2013, 1, 227–236. [Google Scholar]
  62. Shubhankar Niranjan, D.; Bhaskar Dhale, S.; Shekar Mukherjee, J.; Sudhakar Babu, T.; Rajasekar, N. Solar PV array reconfiguration under partial shading conditions for maximum power extraction using genetic algorithm. Renew. Sustain. Energy Rev. 2015, 43, 102–110. [Google Scholar]
  63. Sudhakar Babu, T.; Prasanth Ram, J.; Dragičević, T.; Miyatake, M.; Blaabjerg, F.; Rajasekar, N. Particle swarm optimization based solar PV array reconfiguration of the maximum power extraction under partial shading conditions. IEEE Trans. Sustain. Energy 2017, 9, 74–85. [Google Scholar] [CrossRef]
  64. Raju Pendem, S.; Mikkili, S. Modeling, simulation, and performance analysis of PV array configurations (Series, Series-Parallel, Bridge-Linked, and Honey-Comb) to harvest maximum power under various Partial Shading Conditions. Int. J. Green Energy 2018, 15, 795–812. [Google Scholar] [CrossRef]
  65. Topić, D.; Knežević, G.; Fekete, K. The mathematical model for finding an optimal PV system configuration for the given installation area providing a maximal lifetime profit. Sol. Energy 2017, 144, 750–757. [Google Scholar] [CrossRef]
  66. Sai Krishna, G.; Moger, T. Improved SuDoKu reconfiguration technique for total-cross-tied PV array to enhance maximum power under partial shading conditions. Renew. Sustain. Energy Rev. 2019, 109, 333–348. [Google Scholar] [CrossRef]
  67. Velasco-Quesada, G.; Guinjoan-Gispert, F.; Pique-Lopez, R.; Roman Lumbreras, M.; Conesa-Roca, A. Electrical PV array reconfiguration strategy for energy extraction improvement in grid-connected PV systems. IEEE Trans. Ind. Electron. 2009, 56, 4319–4331. [Google Scholar] [CrossRef] [Green Version]
  68. Nguyen, D.; Lehman, B. A reconfigurable solar photovoltaic array under shadow conditions. In Proceedings of the 23rd Annual IEEE Applied Power Electronics Conference and Exposition, Austin, TX, USA, 24–28 February 2008; pp. 980–986. [Google Scholar]
  69. Rakesh, N.; Madhavaram, T.V. Performance enhancement of partially shaded solar PV array using novel shade dispersion technique. Front. Energy 2016, 10, 227–239. [Google Scholar] [CrossRef]
  70. Patnaik, B.; Sharma, P.; Trimurthulu, E.; Duttagupta, S.P.; Agarwal, V. Reconfiguration strategy for optimization of solar photovoltaic array under non-uniform illumination conditions. In Proceedings of the 37th IEEE Photovoltaic Specialists Conference, Seattle, WA, USA, 19–24 June 2011; pp. 1859–1864. [Google Scholar]
  71. Sagar, G.; Pathak, D.; Gaur, P.; Jain, V. A Su Do Ku puzzle-based shade dispersion for maximum power enhancement of partially shaded hybrid bridge-link-total-cross-tied PV array. Sol. Energy 2020, 204, 161–180. [Google Scholar] [CrossRef]
  72. Pareek, S.; Dahiya, R. Enhanced power generation of partial shaded photovoltaic fields by forecasting the interconnection of modules. Energy 2016, 95, 561–572. [Google Scholar] [CrossRef]
  73. Premkumar, M.; Dhanasekar, N.; Dhivakar, R.; Arunkumar, P. Comparison of MPPT algorithms for PV system-based DC-DC converter. Adv. Nat. Appl. Sci. 2016, 17, 212–221. [Google Scholar]
  74. Kandemir, E.; Cetin, N.S.; Borekei, S. A comprehensive overview of maximum power extraction methods for PV systems. Renew. Sustain. Energy Rev. 2017, 78, 93–112. [Google Scholar] [CrossRef]
  75. Elavarasan, R.M.; Ghosh, A.K.; Mallick, T.; Krishnamurthy, A.; Saravanan, M. Investigations on performance enhancement measures of the bidirectional converter in PV–wind interconnected microgrid system. Energies 2019, 12, 2672. [Google Scholar] [CrossRef] [Green Version]
  76. Premkumar, M.; Sumithira, T.R. Design and implementation of new topology for solar pv based transformerless forward microinverter. J. Electr. Eng. Tech. 2019, 14, 145–155. [Google Scholar] [CrossRef]
  77. Alshareef, M.; Lin, Z.; Ma, M.; Cao, W. Accelerated particle swarm optimization for photovoltaic maximum power point tracking under partial shading conditions. Energies 2019, 12, 623. [Google Scholar] [CrossRef] [Green Version]
  78. Premkumar, M.; Sowmya, R. Certain study on mppt algorithms to track the global MPP under partial shading on solar PV module/array. Int. J. Comput. Digit. Syst. 2019, 8, 405–416. [Google Scholar] [CrossRef]
  79. Pendem, S.R.; Mikkili, S. Modelling and performance assessment of PV array topologies under partial shading conditions to mitigate the mismatching power losses. Sol. Energy 2018, 160, 303–321. [Google Scholar] [CrossRef]
  80. Chan, D.S.H.; Phang, J.C.H. Analytical methods for the extraction of solar-cell single-and double-diode model parameters from I–V characteristics. IEEE Trans. Electron. Dev. 1987, 34, 286–293. [Google Scholar] [CrossRef]
  81. Masters, G.M. Renewable and Efficient Electric Power Systems, 1st ed.; John Wiley & Sons: New Jersey, NJ, USA, 2004; pp. 154–195. [Google Scholar]
  82. Desoto, W.; Beckman, W.; Klein, S. Improvement and validation of a model for photovoltaic array performance. Sol. Energy 2006, 80, 78–88. [Google Scholar] [CrossRef]
  83. Jain, K.; Kapoor, A. Exact analytical solutions of the parameters of real solar cells using Lambert W-function. Sol. Energy Mater. Sol. Cells 2004, 81, 269–277. [Google Scholar] [CrossRef]
  84. Lindholm, F.A.; Fossum, J.G.; Burgess, E.L. Application of the superposition principle to solar-cell analysis. IEEE Trans. Electron Devices 1979, 26, 165–171. [Google Scholar] [CrossRef]
  85. Mihet-Popa, L.; Koch-Ciobotaru, C.; Isleifsson, F.; Bindner, H. Development of tools for simulation systems in a distribution network and validated by measurements. In Proceedings of the 13th International Conference on Optimization of Electrical and Electronic Equipment, Brasov, Romania, 24–26 May 2012; pp. 1022–1031. [Google Scholar]
  86. Koch-Ciobotaru, C.; Mihet-Popa, L.; Isleifsson, F.; Bindner, H. Simulation model developed for a small-scale PV-system in a distribution network. In Proceedings of the 7th International Symposium on Applied Computational Intelligence and Informatics, Timisoara, Romania, 24–26 May 2012; pp. 257–261. [Google Scholar]
  87. Ackermann, T.; Cherevatskiy, S.; Brown, T.; Eriksson, R.; Samadi, A.; Ghandhari, M.; Söder, L.; Lindenberger, D.; Jägemann, C.; Hagspiel, S.; et al. Smart Modeling of Optimal Integration of High Penetration of PV-SMOOTH PV. Available online: http://smooth-pv.info/doc/SmoothPV_Final_Report_Part1.pdf. (accessed on 20 May 2020).
  88. King, D.; Dudley, J.; Boyson, W. PVSIM: A Simulation Program for Photovoltaic Cells, Modules, and Arrays; Sandia National Labs.: Washington, DC, USA, 1996; pp. 1295–1297.
  89. Silvestre, A.B.; Chouder, A. Study of bypass diodes configuration on PV modules. Appl. Energy 2009, 86, 1632–1640. [Google Scholar] [CrossRef]
  90. Hui, L.; Yunmei, C.; Xiangwei, L. Study of bypass diodes configuration on PV modules with partial shaded. In Proceedings of the Chinese Control and Decision Conference, Nanchang, China, 12 September 2019; pp. 511–515. [Google Scholar]
  91. Wei, H.; Liu, F.; Ji, J.; Zhang, S.; Chen, H. Safety analysis of solar module under partial shading. Int. J. Photoenergy 2015, 2015, 907282. [Google Scholar]
  92. Priyadarshi, N.; Padmanaban, S.; Ionel, D.M.; Mihet-Popa, L.; Azam, F. Hybrid PV-Wind, Micro-Grid development using quasi-Z-source inverter modeling and control-Experimental investigation. Energies 2018, 11, 2277. [Google Scholar]
Figure 1. Different photovoltaic (PV) array topologies for the discussions.
Figure 1. Different photovoltaic (PV) array topologies for the discussions.
Energies 13 03216 g001
Figure 2. Solar PV array configurations: (a) series-parallel (SP); (b) total-cross-tied (TCT); (c) honey-comb (HC); (d) bridge-linked (BL); (e) ladder (LD); (f) bridge-linked honey-comb (BLHC); (g) bridge-linked total-cross-tied (BLTCT) and (h) series-parallel total-cross-tied (SPTCT).
Figure 2. Solar PV array configurations: (a) series-parallel (SP); (b) total-cross-tied (TCT); (c) honey-comb (HC); (d) bridge-linked (BL); (e) ladder (LD); (f) bridge-linked honey-comb (BLHC); (g) bridge-linked total-cross-tied (BLTCT) and (h) series-parallel total-cross-tied (SPTCT).
Energies 13 03216 g002
Figure 3. Equivalent PV cell model.
Figure 3. Equivalent PV cell model.
Energies 13 03216 g003
Figure 4. Equivalent circuit of the PV array.
Figure 4. Equivalent circuit of the PV array.
Energies 13 03216 g004
Figure 5. Sketch of different shading patterns under partial shading conditions (PSCs) on HC: (a) uneven column shading (UCS); (b) uneven row shading (URS); (c) uneven corner shading pattern (UCRS); (d) diagonal shading (DS); (e) random shading-I (R-I); (f) random shading-II (R-II) and (g) illustration of solar irradiance levels.
Figure 5. Sketch of different shading patterns under partial shading conditions (PSCs) on HC: (a) uneven column shading (UCS); (b) uneven row shading (URS); (c) uneven corner shading pattern (UCRS); (d) diagonal shading (DS); (e) random shading-I (R-I); (f) random shading-II (R-II) and (g) illustration of solar irradiance levels.
Energies 13 03216 g005
Figure 6. Mathematical analysis of HC array configuration: (a) normal operating condition; (b) uneven row shading condition and (c) uneven column shading condition.
Figure 6. Mathematical analysis of HC array configuration: (a) normal operating condition; (b) uneven row shading condition and (c) uneven column shading condition.
Energies 13 03216 g006
Figure 7. Output characteristics of the SP PV array configuration: (a) current–voltage (I–V) characteristic and (b) power–voltage (P–V) characteristic.
Figure 7. Output characteristics of the SP PV array configuration: (a) current–voltage (I–V) characteristic and (b) power–voltage (P–V) characteristic.
Energies 13 03216 g007
Figure 8. Output characteristics of the TCT PV array configuration: (a) I–V characteristic and (b) P–V characteristic.
Figure 8. Output characteristics of the TCT PV array configuration: (a) I–V characteristic and (b) P–V characteristic.
Energies 13 03216 g008
Figure 9. Output characteristics of the BL PV array configuration: (a) I–V characteristic and (b) P–V characteristic.
Figure 9. Output characteristics of the BL PV array configuration: (a) I–V characteristic and (b) P–V characteristic.
Energies 13 03216 g009
Figure 10. Output characteristics of the HC PV array configuration: (a) I–V characteristic and (b) P–V characteristic.
Figure 10. Output characteristics of the HC PV array configuration: (a) I–V characteristic and (b) P–V characteristic.
Energies 13 03216 g010
Figure 11. Output characteristics of the LD PV array configuration: (a) I–V characteristic and (b) P–V characteristic.
Figure 11. Output characteristics of the LD PV array configuration: (a) I–V characteristic and (b) P–V characteristic.
Energies 13 03216 g011
Figure 12. Output characteristics of the BLHC PV array configuration: (a) I–V characteristic and (b) P–V characteristic.
Figure 12. Output characteristics of the BLHC PV array configuration: (a) I–V characteristic and (b) P–V characteristic.
Energies 13 03216 g012
Figure 13. Output characteristics of the BLTCT PV array configuration: (a) I–V characteristic and (b) P–V characteristic.
Figure 13. Output characteristics of the BLTCT PV array configuration: (a) I–V characteristic and (b) P–V characteristic.
Energies 13 03216 g013
Figure 14. Output characteristics of the SPTCT PV array configuration: (a) I–V characteristic and (b) P–V characteristic.
Figure 14. Output characteristics of the SPTCT PV array configuration: (a) I–V characteristic and (b) P–V characteristic.
Energies 13 03216 g014
Figure 15. Maximum output power generation under shading conditions.
Figure 15. Maximum output power generation under shading conditions.
Energies 13 03216 g015
Figure 16. Comparison between various configurations in terms of RPL.
Figure 16. Comparison between various configurations in terms of RPL.
Energies 13 03216 g016
Figure 17. Comparison between various configurations in terms of RPG.
Figure 17. Comparison between various configurations in terms of RPG.
Energies 13 03216 g017
Table 1. Parameters of SPR-200-BLK-U PV panel.
Table 1. Parameters of SPR-200-BLK-U PV panel.
S. No.ParametersSymbolUnitValue
1Module type--Mono-crystalline silicon
2Number of cellsNse-72
3Voc at standard test condition (STC)VocV47.8
4Isc at STCIscA5.4
5Maximum peak currentImpA5
6Maximum peak voltageVmpV40
7Maximum peak powerPmpW200
8Temperature coefficient on Iscki% / K0.022
9Temperature coefficient on Vockv% mV/K−0.0648
10Series resistanceRse0.2488
11Shunt resistanceRp605.48
12Ideality factora-1.25
Table 2. Results of mathematical analysis.
Table 2. Results of mathematical analysis.
Test CasesIsc (A)In (A)Number of Peaks
Case-I 4 I p h o t o 4 I p h o t o 4 α I p h o t o 2 (1 GP + 1 LP)
Case-II 4 I p h o t o 4 α I p h o t o 3 (1 GP + 2 LPs)
Table 3. PV array output voltage, current and power of different PV configurations.
Table 3. PV array output voltage, current and power of different PV configurations.
ConfigurationsArray Output Voltage (V)Array Output Current (A)Array Output Power (W)
SP V o u t = i = 1 4 V i = 4 V i
i = individual module voltage
I o u t = I j 1 + I j 5 + I j 9 + I j 13 = 4 I j
j = individual string current
P o = 16 × V i × I j
TCT V o u t = V t 1 + V t 2 + V t 3 + V t 4
t = individual row voltage
I o u t = I t 1 + I t 5 + I t 9 + I t 13 = 4 I t
j = individual string current
P o = 16 × V t × I t
BL V o u t = i = 1 4 V i = 4 V i
i = row of the PV array
I o u t = I 1 + I 5 + I 9 + I 13 = 4 I j
j = column of the PV array
P o = 16 × V i × I j
HC V o u t = i = 1 4 V i = 4 V i
i = row of the PV array
I o u t = I 1 + I 5 + I 9 + I 13 = 4 I j
j = column of the PV array
P o = 16 × V i × I j
LD V o u t = i = 1 4 V i = 4 V i
i = row of the PV array
I o u t = I 1 + I 5 + I 9 + I 13 = 4 I j
j = column of the PV array
P o = 16 × V i × I j
BLHC V o u t = i = 1 4 V i = 4 V i
i = row of the PV array
I o u t = I 1 + I 5 + I 9 + I 13 = 4 I j
j = column of the PV array
P o = 16 × V i × I j
BLTCT V o u t = i = 1 4 V i = 4 V i
i = row of the PV array
I o u t = I 1 + I 5 + I 9 + I 13 = 4 I j
j = column of the PV array
P o = 16 × V i × I j
SPTCT V o u t = i = 1 4 V i = 4 V i
i = row of the PV array
I o u t = I 1 + I 5 + I 9 + I 13 = 4 I j
j = column of the PV array
P o = 16 × V i × I j
Table 4. Assessment parameters of PV array configurations under the standard test condition (STC).
Table 4. Assessment parameters of PV array configurations under the standard test condition (STC).
ConfigurationsVoc (V)Isc (A)GP ParametersLP ParametersNo. of LPsML (%)FF (%)
Vmp (V)Imp (A)Pmp (W)Vmp; Imp; Pmp
SP191.421.64159.920.013200--0.03177.32
TCT191.221.62160.419.983200--0.03177.52
BL191.421.64160.319.963200--0.03177.25
HC191.221.64159.920.013200--0.03177.33
LD191.221.64159.920.023200--0.03177.37
BLHC191.221.64160.119.983200--0.03177.31
BLTCT191.221.64159.920.013200--0.03177.33
SPTCT191.221.64159.420.073200--0.03177.32
Table 5. Assessment parameters of PV array configurations under the URS pattern.
Table 5. Assessment parameters of PV array configurations under the URS pattern.
ConfigurationsVoc (V)Isc (A)GP ParametersLP ParametersNo. of LPsML (%)FF (%)
Vmp (V)Imp (A)Pmp (W)Vmp; Imp; Pmp
SP190.221.64119.519.942384167.9;12.31;2068125.5057.89
TCT190.321.59119.319.982384171.7;12.45;2138125.5057.91
BL190.221.64119.519.952384169.6;12.46;2113125.5057.92
HC190.221.64119.419.972384169.7;12.48;2119125.5057.93
LD190.221.63118.820.062384167.8;12.47;2092125.5057.93
BLHC190.221.59119.319.992384170.7; 12.46; 2126125.5058.08
BLTCT190.221.62119.220.012384170.4;12.48;2126125.5058.00
SPTCT190.221.63119.220.012384170.2;12.45;2120125.5057.98
Table 6. Assessment parameters of PV array configurations under UCS pattern.
Table 6. Assessment parameters of PV array configurations under UCS pattern.
ConfigurationsVoc (V)Isc (A)GP ParametersLP ParametersNo. of LPsML (%)FF (%)
Vmp (V)Imp (A)Pmp (W)Vmp; Imp; Pmp
SP190.521.05161.516.962740131.1; 18.40; 2412
85.55; 19.23; 1645
38.48; 20.46; 787.3
314.3768.30
TCT190.521.01163.217.532859120; 18.49; 2219
75.24; 19.68; 1483
210.6571.48
BL190.521.09162.317.022791125.8; 18.55; 2334
78.03; 1534; 19.65
37.61; 20.52; 771.2
312.7868.76
HC190.521.08163.217.272819122.6; 18.28; 2240
83.15; 19.36; 1610
211.9170.19
LD190.521.09163.117.112791125; 18.49; 2310
79.71; 19.66; 1567
35.38; 20.55; 727.1
312.7869.46
BLHC190.521.0816317.442842121.3; 18.62; 2258
76.12; 19.62; 1493
211.1970.79
BLTCT190.521.08163.817.352841122.3; 18.45; 2257
74.37; 19.73; 1468
36.33; 20.36; 740
311.2270.77
SPTCT190.521.05162.917.342825123.4; 18.59; 2295
73.73; 19.72; 1454
37.34; 20.48; 764.9
311.7270.44
Table 7. Assessment parameters of PV array configurations under the UCRS pattern.
Table 7. Assessment parameters of PV array configurations under the UCRS pattern.
ConfigurationsVoc (V)Isc (A)GP ParametersLP ParametersNo. of LPsML (%)FF (%)
Vmp (V)Imp (A)Pmp (W)Vmp; Imp; Pmp
SP190.421.64163.516.032621130.7; 18.01; 2354
84.51; 19.65; 1661
218.0963.61
TCT190.621.58165.716.752748121.4; 18.5; 2246
78.28; 20.03; 1568
214.1367.48
BL190.521.64164.316.322682125.8; 18.05; 2334
84.4; 19.68; 1661
216.1965.04
HC190.121.63164.716.62734122.6; 18.39; 2255
80.29; 19.82; 1592
214.5666.49
LD190.621.6316516.452714124.8; 18.22; 2275
81.72; 19.6; 1602
215.1965.84
BLHC190.621.63165.916.52738122.2; 18.48; 2259
78.33; 20.02; 1568
214.4466.40
BLTCT190.621.63165.416.552738122.8; 18.34; 2253
79.35; 19.97; 1585
214.4466.40
SPTCT190.421.63164.516.352690123.7; 18.29; 2263
82.71; 19.91; 1647
215.9465.31
Table 8. Assessment parameters of PV array configurations under the DS pattern.
Table 8. Assessment parameters of PV array configurations under the DS pattern.
ConfigurationsVoc (V)Isc (A)GP ParametersLP ParametersNo. of LPsML (%)FF (%)
Vmp (V)Imp (A)Pmp (W)Vmp; Imp; Pmp
SP190.421.63118.720.082384167.9;13.36;2243125.557.87
TCT190.621.01162.817.512851117.3;16.2;2192
35.75;19.58;718.6
210.9071.18
BL190.521.64119.319.982384168.3;13.5;2273125.5057.82
HC191.321.08162.217.352815122.5;18.52;2268
38.11;20.03;763.2
212.0369.79
LD190.521.63165.916.032660121;17.98;2176
80.8;19.83;1602
216.8864.54
BLHC190.621.08162.817.492849119;18.47;2198
37.42;20.18;755.2
210.9770.87
BLTCT190.621.08162.617.422833122;18.34;2237
37.85;20.07;759.9
211.4770.50
SPTCT190.421.58165.515.352541122.7;18.32;2249
82.71;19.91;1647
220.5961.83
Table 9. Assessment parameters of PV array configurations under the R-I pattern.
Table 9. Assessment parameters of PV array configurations under the R-I pattern.
ConfigurationsVoc (V)Isc (A)GP ParametersLP ParametersNo. of LPsML (%)FF (%)
Vmp (V)Imp (A)Pmp (W)Vmp; Imp; Pmp
SP189.721.03164.113.262177125.5; 15.87; 1992
80.17; 16.65; 1335
39.26; 19.53; 767.1
331.9654.54
TCT189.820.48165.114.52394121.3; 15.88; 1926
37.58; 19.02; 714.7
225.1861.59
BL189.820.54164.414.32352126; 15.55; 1959
81.33; 16.71; 1359
38.34; 18.97; 727.3
326.5060.30
HC189.820.54166.513.422235124; 15.76; 1955
80.84; 17.07; 1380
39.22; 19.03; 746.3
330.1657.32
LD189.721.08163.113.412187125.8; 15.95; 2006
39.23; 19.18; 752.5
231.6654.69
BLHC189.720.54164.614.512389120.4; 15.86; 1910
39.28; 18.63; 731
225.3461.30
BLTCT189.721.08165.413.942306122.5; 15.88; 1946
80.66; 16.94; 1367
39.19; 18.66; 731.1
327.9457.66
SPTCT189.721.03165.513.882298122.6; 15.82; 1940
81.76; 16.91; 1383
37.98; 19.14; 727
328.1957.58
Table 10. Assessment parameters of PV array configurations under the R-II pattern.
Table 10. Assessment parameters of PV array configurations under the R-II pattern.
ConfigurationsVoc (V)Isc (A)GP ParametersLP ParametersNo. of LPsML (%)FF (%)
Vmp (V)Imp (A)Pmp (W)Vmp; Imp; Pmp
SP189.621.62123.914.421787171.6;9.35;1606
79.54;18.331458
38.12;19.7;751.2
344.1543.58
TCT189.521.5616711.77196679.13;18.42;1458
38.24;20.01;750.6
238.5648.11
BL189.421.62125.213.931744170.9;9.878;1688
79.68;18.3;1458
37.61;19.99;752.6
345.5042.59
HC189.521.62168.511.371915124.4;12.47;1553
79.48;18.18;1458
37.73;19.94;752.1
340.1646.76
LD189.521.62167.811.441920125.8;12.42;1563
79.71;18.29;1458
37.6;20;752.1
340.0046.85
BLHC189.521.62166.211.83196679.69;18.3;1458
37.42;20.09;751.7
238.5647.99
BLTCT189.521.62168.211.421922125.8;12.44;1565
79.43;18.36;1458
37.17;20.2;750.6
339.9446.88
SPTCT189.621.62124.614.471803171.6;9.37;1608
79.32;18.38;1458
37.34;20.12;751.4
343.6643.98
Table 11. Relative power loss (RPL) comparison of various array topologies.
Table 11. Relative power loss (RPL) comparison of various array topologies.
ConfigurationsURS
(Pthe = 2880 W)
UCS
(Pthe = 2940 W)
UCRS
(Pthe = 2960 W)
DS
(Pthe = 2920 W)
RS-1
(Pthe = 2580 W)
RS-2
(Pthe = 2440 W)
Pmp
(W)
RPL
(W)
Pmp
(W)
RPL
(W)
Pmp
(W)
RPL
(W)
Pmp
(W)
RPL
(W)
Pmp
(W)
RPL
(W)
Pmp
(W)
RPL
(W)
SP238449627402002621339238453621774031787653
TCT2384496285981274821228516923941861966474
BL238449627911492682278238453623522281744696
HC238449628191212734226281510522353451915525
LD238449627911492714246266026021873931920520
BLHC2384496284298273822228497123891911966474
BLTCT2384496284199273822228338723062741922518
SPTCT238449628251152690270254137922982821803637
Bold values point toward the best performance of PV array configurations.
Table 12. Relative power gained (RPG) comparison of various array topologies.
Table 12. Relative power gained (RPG) comparison of various array topologies.
ConfigrationsURSUCSUCRSDSRS-1RS-2
Pmp
(W)
RPG
(%)
Pmp
(W)
RPG
(%)
Pmp
(W)
RPG
(%)
Pmp
(W)
RPG
(%)
Pmp
(W)
RPG
(%)
Pmp
(W)
RPG
(%)
SP238402740026210238402177017870
TCT2384028594.3427484.85285119.5823949.96196610.01
BL2384027911.8626822.3323840.0023528.041744−2.41
HC2384028192.8827344.31281518.0822352.6619157.16
LD2384027911.8627143.55266011.5821870.4619207.44
BLHC2384028423.7227384.46284919.5123899.74196610.02
BLTCT2384028413.6927384.46283318.8323065.9319227.55
SPTCT2384028253.1026902.6325416.5922985.5618030.90
Bold values point toward the best performance of PV array configurations.

Share and Cite

MDPI and ACS Style

Premkumar, M.; Subramaniam, U.; Babu, T.S.; Elavarasan, R.M.; Mihet-Popa, L. Evaluation of Mathematical Model to Characterize the Performance of Conventional and Hybrid PV Array Topologies under Static and Dynamic Shading Patterns. Energies 2020, 13, 3216. https://doi.org/10.3390/en13123216

AMA Style

Premkumar M, Subramaniam U, Babu TS, Elavarasan RM, Mihet-Popa L. Evaluation of Mathematical Model to Characterize the Performance of Conventional and Hybrid PV Array Topologies under Static and Dynamic Shading Patterns. Energies. 2020; 13(12):3216. https://doi.org/10.3390/en13123216

Chicago/Turabian Style

Premkumar, Manoharan, Umashankar Subramaniam, Thanikanti Sudhakar Babu, Rajvikram Madurai Elavarasan, and Lucian Mihet-Popa. 2020. "Evaluation of Mathematical Model to Characterize the Performance of Conventional and Hybrid PV Array Topologies under Static and Dynamic Shading Patterns" Energies 13, no. 12: 3216. https://doi.org/10.3390/en13123216

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop